References

1. 1.
   Breiman L. 1996. Bagging predictors. Machine Learning, 24(2): 123-140
2. 2.
   Breiman L. 2001. Random forests. Machine Learning, 45(1): 5-32
3. 3.
   Chen A X and Li Y C. 2020. Rice recognition of different growth stages based on Sentinel-2 images in mountainous areas of Southwest China. Transactions of the Chinese Society of Agricultural Engineering, 36(7): 192-199
4. 4.
   Chen J, Chen J, Liao A P, Cao X, Chen L J, Chen X H, He C Y, Han G, Peng S, Lu M, Zhang W W, Tong X H and Mills J. 2015. Global land cover mapping at 30 m resolution: a POK-based operational approach. ISPRS Journal of Photogrammetry and Remote Sensing, 103: 7-27
5. 5.
   Clevers J G P W and Gitelson A A. 2013. Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3. International Journal of Applied Earth Observation and Geoinformation, 23: 344-351
6. 6.
   Dash J and Curran P J. 2004. The MERIS terrestrial chlorophyll index. International Journal of Remote Sensing, 25(23): 5403-5413
7. 7.
   Elvidge C D and Chen Z K. 1995. Comparison of broad-band and narrow-band red and near-infrared vegetation indices. Remote Sensing of Environment, 54(1): 38-48
8. 8.
   Fang F P and Cheng S H. 2018. The development of rice science, technology and industry in China. Journal of Agriculture, 8(1): 100-106
9. 9.
   Feng R, Yu W Y, Ji R P, Zhang Y S, Wu J W and Chen P S. 2017. Comparison and analysis of several extraction methods for lakes and reservoirs based on FY3B/MERSI. Science of Surveying and Mapping, 42(7): 147-152
10. 10.
    He Y, Huang C, Li H, Liu Q S, Liu G H, Zhou Z C and Zhang C C. 2019. Land-cover classification of random forest based on Sentinel-2A image feature optimization. Resources Science, 41(5): 992-1001
11. 11.
    Horler D N H, Dockray M and Barber J. 1983. The red edge of plant leaf reflectance. International Journal of Remote Sensing, 4(2): 273-288
12. 12.
    Hou M J, Yin J P, Ge J, Li Y C, Feng Q S and Liang T G. 2020. Land cover remote sensing classification method of alpine wetland region based on random forest algorithm. Transactions of the Chinese Society for Agricultural Machinery, 51(7): 220-227
13. 13.
    Huang J W, Li Z Y, Chen E X, Zhao L and Mo B P. 2021. Classification of plantation types based on WFV multispectral imagery of the GF-6 satellite. Journal of Remote Sensing, 25(2): 539-548
14. 14.
    Huang J X, Hou Y Z, Su W, Liu J M and Zhu D H. 2017. Mapping corn and soybean cropped area with GF-1 WFV data. Transactions of the Chinese Society of Agricultural Engineering, 33(7): 164-170
15. 15.
    Immitzer M, Vuolo F and Atzberger C. 2016. First experience with Sentinel-2 data for crop and tree species classifications in central Europe. Remote Sensing, 8(3): 166
16. 16.
    Jia K, Li Q Z, Tian Y C and Wu B F. 2011. A review of classification methods of remote sensing imagery. Spectroscopy and Spectral Analysis, 31(10): 2618-2623
17. 17.
    Kim H O and Yeom J M. 2014. Effect of red-edge and texture features for object-based paddy rice crop classification using RapidEye multi-spectral satellite image data. International Journal of Remote Sensing, 35(19): 7046-7068
18. 18.
    Li Q J, Liu J, Mi X F, Yang J and Yu T. 2021. Object-oriented crop classification for GF-6 WFV remote sensing images based on Convolutional Neural Network. National Remote Sensing Bulletin, 25(2): 549-558
19. 19.
    Li W J, Guo X L, Yang L B, Yan M, Zou C X, Fang Y H, Sun H and Huang J F. 2020. Accurate recognition of wine grapes using multi-feature optimization based on GF-6 satellite images. Transactions of the Chinese Society of Agricultural Engineering, 36(18): 165-173
20. 20.
    Li Z P, Liu Z H, Li Z G, Tang P Q, Tan J Y and Yang P. 2014. Progress and prospect of application of remote sensing to rice spatial distribution. Chinese Journal of Agricultural Resources and Regional Planning, 35(6): 9-18
21. 21.
    Liang J, Zheng Z W, Xia S T, Zhang X T and Tang Y Y. 2020. Crop recognition and evaluation using red edge features of GF-6 satellite. Journal of Remote Sensing (Chinese), 24(10): 1168-1179
22. 22.
    Lu C L, Bai Z G, Li Y C, Wu B, Di G D and Dou Y F. 2021. Technical characteristic and new mode applications of GF-6 satellite. Spacecraft Engineering, 30(1): 7-14
23. 23.
    Lu D, Fu X J and Yue M J. 2020. Development status and policy suggestions of rice industry in Liaoning Province. Liaoning Agricultural Sciences, (6): 57-59
24. 24.
    Mehdaoui R and Anane M. 2020. Exploitation of the red-edge bands of Sentinel 2 to improve the estimation of durum wheat yield in Grombalia region (Northeastern Tunisia). International Journal of Remote Sensing, 41(23): 8986-9008
25. 25.
    Su W, Zhao X F, Sun Z P, Zhang M Z, Zou Z C, Wang W and Shi Y L. 2019. Estimating the corn canopy chlorophyll content using the Sentinel-2A image. Spectroscopy and Spectral Analysis, 39(5): 1535-1542
26. 26.
    Sun M X, Liu M, Sun Q Q, Zhang P, Jiao X, Sun D F and Shi Y Y. 2020. Response of new bands in GF-6 to land use/cover based on linear spectral mixture analysis model. Transactions of the Chinese Society of Agricultural Engineering, 36(3): 244-253
27. 27.
    Wang L J, Kong Y R, Yang X D, Xu Y, Liang L and Wang S G. 2020. Classification of land use in farming areas based on feature optimization random forest algorithm. Transactions of the Chinese Society of Agricultural Engineering, 36(4): 244-250
28. 28.
    Yan L and Jiang W W. 2016. Progress in the study of vegetation cover classification of multispectral remote sensing imagery. Remote Sensing for Land and Resources, 28(2): 8-13
29. 29.
    Yang J Y, Zhou Z X, Du Z R, Xu Q Q, Yin H and Liu R. 2019. Rural construction land extraction from high spatial resolution remote sensing image based on SegNet semantic segmentation model. Transactions of the Chinese Society of Agricultural Engineering, 35(5): 251-258
30. 30.
    Zhang P and Hu S G. 2019. Fine crop classification by remote sensing in complex planting areas based on field parcel. Transactions of the Chinese Society of Agricultural Engineering, 35(20): 125-134
31. 31.
    Zhang Q Y, Li Z, Xia C Z, Chen J and Peng D L. 2019. Tree species classification based on the new bands of GF-6 remote sensing satellite. Journal of Geo-Information Science, 21(10): 1619-1628